Exploring Class Enumeration in Bayesian Growth Mixture Modeling Based on Conditional Medians
Frontiers in Education, 2021 Growth mixture modeling is a popular analytic tool for longitudinal data analysis. It detects latent groups based on the shapes of growth trajectories.
Seohyun Kim, Xin Tong, Zijun Ke
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Latent trajectory studies: the basics, how to interpret the results, and what to report [PDF]
European Journal of Psychotraumatology, 2015 Background: In statistics, tools have been developed to estimate individual change over time. Also, the existence of latent trajectories, where individuals are captured by trajectories that are unobserved (latent), can be evaluated (Muthén & Muthén, 2000)
Rens van de Schoot
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Analysis of heterogeneous growth changes in longitudinal height of children
Journal of Health, Population and Nutrition, 2023 Background There have been methodologies developed for a wide range of longitudinal data types; nevertheless, the conventional growth study is restricted if individuals in the sample have heterogeneous growth trajectories across time.
Senahara Korsa Wake +2 more
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Model Fit and Comparison in Finite Mixture Models: A Review and a Novel Approach
Frontiers in Education, 2021 One of the greatest challenges in the application of finite mixture models is model comparison. A variety of statistical fit indices exist, including information criteria, approximate likelihood ratio tests, and resampling techniques; however, none of ...
Kevin J. Grimm +2 more
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An Introduction to Latent Variable Mixture Modeling (Part 2): Longitudinal Latent Class Growth Analysis and Growth Mixture Models [PDF]
Journal of Pediatric Psychology, 2013 Pediatric psychologists are often interested in finding patterns in heterogeneous longitudinal data. Latent variable mixture modeling is an emerging statistical approach that models such heterogeneity by classifying individuals into unobserved groupings (latent classes) with similar (more homogenous) patterns.
Berlin, Kristoffer S. +2 more
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Effects of growth trajectory of shock index within 24 h on the prognosis of patients with sepsis
Frontiers in Medicine, 2022 BackgroundSepsis is a serious disease with high clinical morbidity and mortality. Despite the tremendous advances in medicine and nursing, treatment of sepsis remains a huge challenge. Our purpose was to explore the effects of shock index (SI) trajectory
Fengshuo Xu +13 more
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Heliyon, 2022 Introduction: The progression of complications of type 2 diabetes (T2D) is unique to each patient and can be depicted through individual temporal trajectories.
Sarah O'Connor +5 more
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Understanding Variation in Longitudinal Data Using Latent Growth Mixture Modeling
Journal of Pediatric Psychology, 2021 Abstract Objective This article guides researchers through the process of specifying, troubleshooting, evaluating, and interpreting latent growth mixture models. Methods Latent growth mixture models are conducted with small example ...
Constance A, Mara, Adam C, Carle
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Residual-Based Algorithm for Growth Mixture Modeling: A Monte Carlo Simulation Study
Frontiers in Psychology, 2021 Growth mixture models are regularly applied in the behavioral and social sciences to identify unknown heterogeneous subpopulations that follow distinct developmental trajectories.
Katerina M. Marcoulides, Laura Trinchera
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What Applying Growth Mixture Modeling Can Tell Us About Predictors of Number Line Estimation
Journal of Numerical Cognition, 2020 Number line estimation tasks have been considered a good indicator of mathematical competency for many years and are traditionally analyzed by fitting individual regression curves to individual responders. We innovate on this technique by applying growth
Jeffrey M. DeVries +2 more
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